Data Visualization
Business Intelligence & Analytics
Jul 08, 2021
Alba Mañanes Rodríguez
Technical Marketing Consultant
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The keys to an intelligent and practical data visualization framework, plus the tools you need to succeed

Home > Business Intelligence & Analytics > The keys to an intelligent and practical data visualization framework, plus the tools you need to succeed
What good is data if we are unable to interpret it? Only when we can apply meaning to the numbers does it become knowledge. With so much data to analyze, it has become almost impossible to organize and, in turn, draw any significant conclusions. The solution? Technology. And specifically, data visualization tools.

We live in an informational age where we are constanly exposed to stimuli that our brain interprets and analyzes to make decisions. Our consuption has multiplied in recent years as more and more information is produced (via social networks, mobile devices, etc.,), and we gain easier access to its consumption thanks to the internet. 

In 2021, the average time of daily internet usage was around 190 minutes, a figure that continues to grow year over year. Our life is has become increasingly digital, as we produce and consume significantly more data. However, with more data comes more opportunities to leverage and extract critical insights.

This same logic is applied to the corporate world. Companies obtain and store enormous amounts of data around their customer base but do not have the necessary tools or knowledge to make actional decisions with this information.

Data visualization tools

Data, as isolated statistics, does not provide any concrete meaning or offer any significant value. If, as companies or individuals, we cannot extract information from the data, it is useless. For this reason, we have to find a way to create data visualization frameworks that can interpret the data for us, in turn allowing us to convert database information into actual clients.

Why do you need data visualization? Grow your business!

Sometimes a picture is worth a thousand words - or in this case, more than a thousand datasheets. 

All professional sectors can benefit from making their graphical data displays more understandable. 

The well-known and straightforward graphs (charts, tables, maps, dashboards) serve as an essential foundation, but now there are heat maps, area graphs, cartograms, histograms, highlight tables, and matrices (to name a few). They are more complex evolutions that, with the appropriate analysis techniques, can show significant insights.

A data visualization dashboard is helpful for many reasons, primarily for client-facing companies looking to improve customer management. Working on a client's database and showing them significant insights (that, in turn, translate to actionable items) will be much easier to promote internal change and growth. 

Salesforce business dashboard

Fuente: Salesforce

It also helps with strategic planning and real-time monitoring. Observing the present data allows us to modify actions according to results to achieve any long-term project vision. The only way to grow is by paying attention to the performance of each campaign, and this is where data visualization becomes extremely helpful.

In the world of Big Data, the tools and technologies that allow us to create these graphical data displays are essential to analyze large amounts of information, draw conclusions and make decisions based on truthful figures.

Types of Data Visualization

There is a multitude of analysis techniques and approaches depending on the nature of the data. In general, we can establish three types of graphical data displays.

  1. Basic elements of data representation. A basic visualization element can be a chart, map, data table, graph, etc.

  2. Control panel. It is a complex composition of individual visualizations that keep coherence and a thematic relationship between them. They are widely used in organizations for the analysis of sets of variables and decision-making.

  3. Infographics. A composition of visualizations that builds, from different elements, a complex meaning for the user. These are more focused on the construction of narratives from data, that is, to tell stories.

How does the data science and visualization process work?

In the case of a metrics and conclusions presentation, in which we present the Goals & Metrics of a company, we can follow these steps:

  1. Obtaining the data

Google Analytics is the tool used by many companies for data analysis. It provides us with an overview of everything on our website, allowing us to understand both our client behavior and that as a company.  

Included among the most interesting data:

  • Web traffic (separating the blog as an independent element when measuring)

  • Bounce rate

  • Page duration

  • News users

  • Returning users

  • Traffic divided according to the source of origin (organic, direct, paid, referrals, social and email)

  • Social media traffic 

  • PPC performance

  • SEO results and/or actions

  • The posts within the blog (if any) that receive the most visits

 

  1. Data Organization

Once we have obtained the data, the key is to group them in the same document (Excel, for example) to keep a complete record of its evolution and have an updated database with all the information relevant to the project.

 How to improve data visualization

 

  1. Preparation of the report to facilitate the visualization of the data

At this point, we have all the necessary data. However, it is essential to transform it into easy-to-understand conclusions and present them in an attractive, visual way.

 

Data visualization tools: integration is key!

Technological advances have gone hand in hand with new ways of displaying and analyzing data.

Data visualization with Tableau is an excellent example of this: this tool is a visual analytics platform leveraged to get the most out of data, with real-time business dashboards and a multitude of visualization options (charts, tables, graphs, maps, etc.) with which you can create a personalized interface based on specific needs. With Tableau Business Intelligence we add value to our data.

Integration is another significant trend seen in data visualization. In a multichannel world, where users can communicate with companies through various platforms (and companies, in turn, use different applications to collect and manage said information), Mulesoft is the answer.

It is a systems integration software that, through APIs, connects several applications simultaneously, allowing them to exchange data in real-time. This technology facilitates the implementation of multi-system business processes and obtains a 360º view of clients, services, products, employees, etc., saving a lot of time. Centralizing information is essential for the analysis and visualization of data.

Both tools (Tableau and Mulesoft) are part of the Salesforce ecosystem. Tableau extends Salesforce services with new dashboards and real-time reports that, combined with Salesforce Einstein Artificial Intelligence, opens up a new world of possibilities. Mulesoft connects all data sources in an agile, efficient, and secure way. The most powerful data analysis techniques are in Salesforce.

Tips for optimal data visualization

In general, when it is time to present the data extracted during the analysis process, we recommend following these guidelines:

  • Use a suitable graphic. Not everyone communicates the same, be sure you are presenting your data in the right way. 

  • Highlight the essential information. It helps a reader efficiently process the presented information and conclusions.

  • Avoid the representation of data using tables. If you must use them, include distinctive colors, sizes, and elements that facilitate their understanding.

  • Focus on drawing conclusions. Ultimately, this is paramount in the analytical process.

  • Give guidelines for improvement in each of the metrics analyzed.

  • Highlight the positive and the negative. We can learn lessons from both: actions that have led to positive ratios should be highlighted, as well as the negative.

  • Bring together the parties involved in improving the process. We are offering an overview to all those who participate in the evolution and development of the company.

  • Favor an environment of proactivity and participation. The most important thing when it comes to visualizing the data is getting improvements and providing feedback on the process.

  • Propose next steps or improvement objectives for the next period.

  • Make comparisons of both previous months and years prior to the current one, to identify and measure trends.

Data visualization is a powerful tool for transmitting information and drawing conclusions. It is essential to develop and find the formula that can get you the most out of it with the segmentation of databases and appropriate visualization technologies.

Implementing specific tools for data visualization is the fastest and most productive way to solve this challenge. Business Intelligence consultancies are an essential ally in the digital transformation of the business environment. At WAM Global, we can help you use platforms to raise your business intelligence. Because, as you now know, a picture is worth a thousand words.

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